School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Victorian Melanoma Service, Alfred Hospital, 55 Commercial Road, Melbourne, VIC, 3004, Australia.
Am J Clin Dermatol. 2021 Mar;22(2):233-242. doi: 10.1007/s40257-020-00574-4.
Artificial intelligence (AI) algorithms have been shown to diagnose skin lesions with impressive accuracy in experimental settings. The majority of the literature to date has compared AI and dermatologists as opponents in skin cancer diagnosis. However, in the real-world clinical setting, the clinician will work in collaboration with AI. Existing evidence regarding the integration of such AI diagnostic tools into clinical practice is limited. Human factors, such as cognitive style, personality, experience, preferences, and attitudes may influence clinicians' use of AI. In this review, we consider these human factors and the potential cognitive errors, biases, and unintended consequences that could arise when using an AI skin cancer diagnostic tool in the real world. Integrating this knowledge in the design and implementation of AI technology will assist in ensuring that the end product can be used effectively. Dermatologist leadership in the development of these tools will further improve their clinical relevance and safety.
人工智能（AI）算法在实验环境中已经被证明可以非常准确地诊断皮肤病变。迄今为止，大多数文献都将 AI 和皮肤科医生作为皮肤癌诊断的对手进行了比较。然而，在现实的临床环境中，临床医生将与 AI 合作。关于将此类 AI 诊断工具整合到临床实践中的现有证据有限。人类因素，如认知风格、个性、经验、偏好和态度，可能会影响临床医生对 AI 的使用。在这篇综述中，我们考虑了这些人为因素，以及在现实世界中使用 AI 皮肤癌诊断工具时可能出现的潜在认知错误、偏差和意外后果。在设计和实施 AI 技术时整合这些知识将有助于确保最终产品能够得到有效使用。皮肤科医生在这些工具的开发中的领导作用将进一步提高其临床相关性和安全性。
